Robust data is an essential underwriting tool
In a sector rife with market volatility and other unknowns, Big Oil often carries outsized exposures. Unlike general property insurance for commercial enterprises, where the law of large numbers sharpens underwriting for more than 5 million buildings, data on the roughly 135 oil and gas refineries operating in the United States is relatively slim. The energy insurance market is highly segmented and available information is often piecemeal, making it challenging to assess future outcomes.
When a claim occurs, severity tends to be high, given the value of the assets. And the likelihood of business interruption due to an accident magnifies the impact of even small events. To underwrite these complex operations, insurers need robust data. That data can help them in several ways, including portfolio assessment, strategic planning, and underwriting.
Success in property/casualty insurance begins with the law of large numbers. Put simply, this axiom generally provides that the more exposure units included in an analysis, the more accurate a loss prediction should be. This presents a challenge for underwriters because energy insurance is highly segmented by territory, line of business, and production process.
Consider the following facts about refineries. There are 898 oil refineries in the world, of which 737 are presently operational, according to the latest data from Wood Mackenzie, a leading source of information about energy and natural resources sectors. Of the refineries considered to be operational, only 135 are located in the United States.
Refinery exposures also differ based on the industrial processes involved. A topping refinery is the simplest kind of oil refinery—it only separates crude oil into its main components. A hydroskimming refinery distills and reforms to produce gasoline and is therefore a more complex operation than a topping refinery. A highly complex cracking and coking refinery converts fuel oil into light distillates (liquefied petroleum gas, gasoline, naphtha) or petroleum coke, which has many applications and is used as a fuel in the metals and brick industries.
The relatively small number of highly diverse refineries makes it difficult to find patterns, make comparisons, and draw accurate conclusions. This holds true not only for refineries, but for many energy segments and assets. It also renders the law of large numbers almost meaningless, as there often aren’t enough exposure units in relation to a specific loss experience.
For insurers to analyze and structure their portfolios effectively, they may need to reduce the segmentation of information and look at a wider universe of available data points. By evaluating all 898 refineries in their underwriting analysis, insurers are incorporating a larger pool of data, making it easier to find patterns among operators and benchmark across regions. Armed with information, they also can often better compare their performance to peers and begin to understand where there may be room for improvement.
One solution would be a platform for the energy insurance industry to score, analyze, and benchmark risks.
Energy underwriters have learned that insuring better quality risks doesn’t always translate to better loss ratios. Even the best-rated assets can report losses that carry potential costs amounting to hundreds of millions of dollars. With a better understanding of the landscape of possible risks—along with an assessment of weaknesses, strengths, and the market’s financial outlook—underwriters also can balance their exposures and plan how and where to deploy their capacity.
Identifying areas for improvement is only the first step. Energy insurers also need to chart a course for success by finding the right opportunities in an increasingly complex and volatile environment. Discovering new opportunities begins with data—and an in-depth understanding of the financial health of each of the insureds within a supply chain.
Finding the “right” opportunity also requires targeting the right market segment, territory, and risks. Industrywide market research tends to be scarce because insurers typically rely on internal experts and experience to inform their decisions. That can mean pursuing markets—based on intuition—that an insurer believes will yield the greatest rewards in the shortest period of time with the smallest investment of resources. But even best guesses can be off the mark. For success, the key may be the use of robust market analysis based on multiple criteria to uncover optimal market segments.
The ultimate use of data comes in executing a strategic plan. As even small property losses hold potential for a catastrophic effect on an energy insurer’s portfolio, underwriting precision remains critical.
For example, energy risk exposures can vary significantly by location. Assets in some areas—offshore or along coasts, for example—may be more vulnerable to natural disasters. Others may be located in communities with more pressing environmental concerns. Even the distinct cultures of countries in which a risk is being operated can affect the quality and integrity of operations.
How do these differences translate into rating and premiums, credits or debits, and frequency or severity? How can an insurer integrate physical risk factors, such as an asset’s age or processes, along with soft factors, such as the culture of the country or the operator’s financial history?
To help determine pricing, insurers of energy assets trust teams of engineers to assess each potential risk thoroughly. Such analyses and recommendations can be invaluable to the underwriter—the player who needs to understand and evaluate the soft factors to make pricing and structuring decisions. But it may be nearly impossible for engineers to visit all locations regularly and provide enough up-to-date information.
There’s also the question of underwriting expenses. Continual investigation and reporting can add significantly to costs and time for underwriting energy risks, making it even harder for insurers to reduce their expense ratios. Access to a single source of data and relevant analytics for handling the risks and exposures from each potential asset, portfolio, or region could help streamline the underwriting process, improve insurer loss and expense ratios, and potentially allow for more rapid market expansion.
One solution would be a platform for the energy insurance industry to score, analyze, and benchmark risks. Such a solution would need to be organized around a core energy, power, and mining value chain and bring to insurers the potential for delivering up-to-date and accurate information in an operationally and cost-efficient manner.
Elizabeth Casas Leano is managing director of energy and insurance at Verisk Insurance Solutions, a Verisk Analytics (Nasdaq:VRSK) business.
To learn more, visit www.verisk.com/insurance/energy.html